Garment customization order processing method and system

Abstract

The invention provides a garment customization order processing method and system, and relates to the technical field of computers. The method comprises the following steps: acquiring protocol data of a target order, wherein the protocol data carries a protocol countersigning instruction; when a protocol countersigning result is detected to be that the electronic protocol is reached, order data is generated based on the protocol data, and the protocol countersigning result is generated after other countersigning terminals respond to the protocol countersigning instruction to perform countersigning; when it is detected that the order data meets any order re-planning condition, a countersigning adjustment instruction is initiated and then issued to a countersigning terminal, and the order re-planning condition comprises a demand abnormal condition corresponding to order demand data indicated by the order data and a demand change condition corresponding to the protocol data; and on the basis of the countersigning adjustment result, order data of the target order is regenerated, production is carried out according to the updated order data, and the countersigning adjustment result is generated after the countersigning terminal responds to the countersigning adjustment instruction to carry out countersigning. The production efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for processing clothing customization orders. Background Art

[0002] As consumers’ demand for customized services increases, traditional order management models are unable to adapt to complex and diverse personalized customization needs, especially in order confirmation, production planning and supply chain collaboration. Many problems are exposed, often leading to low production efficiency, delayed delivery and reduced customer satisfaction. At the same time, customized orders involve the collaborative work of multiple departments and links, including marketing, supply, production, quality control and after-sales service, and each department has different operational requirements for orders, resulting in obvious information islands and inefficient communication.

[0003] At present, the existing clothing production processing methods involve order management systems and agreement countersignature systems, which are essentially two independently running systems, that is, the order management system is responsible for the creation, sorting, and destruction of production orders, and the agreement countersignature system is responsible for remittance, pattern making, and pattern finalization. The existing methods can meet most of the needs of clothing production because most of the orders for clothing production are large-volume orders with fixed sizes and types. If there are no unexpected situations such as order cancellations, the agreement countersignature system and the order management system will not have much interaction in business logic, so even if the two systems run independently, they will not affect production efficiency.

[0004] However, as the number of customized clothing orders gradually increases, these customized orders are usually small batches and diversified production. When users need to change the size or style during production, the agreement signing system and the order management system need to be modified at the same time. In this regard, the existing agreement signing system and order management system may be out of sync due to their independent operation, resulting in production errors, which greatly affects production efficiency. Summary of the invention

[0005] In order to solve the above-mentioned problems in the prior art, the present invention provides a method and system for processing customized clothing orders, which can improve production efficiency.

[0006] In a first aspect, the present application provides a method for processing a clothing customization order, which is used for processing equipment, comprising: Acquire the agreement data of the target order, wherein the agreement data carries the agreement countersigning instruction initiated from any countersigning terminal; When it is detected that the agreement countersigning result is that the electronic agreement corresponding to the target order has been reached, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction; When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data; Based on the obtained adjustment counter-signing result, the order data of the target order is regenerated, and production is performed according to the updated order data, wherein the adjustment counter-signing result is generated after the counter-signing terminal responds to the adjustment counter-signing instruction and counter-signs.

[0007] In a possible implementation, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, and the interactive audio data is used to record the voice communication process for the electronic agreement and / or the target order; the method further includes: When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, an intention analysis is performed on the interactive audio data of the target order; When it is analyzed that the electronic agreement meets the preset condition of the tendency to achieve the goal, the target order is added to the waiting queue; Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data; Clearing the target order corresponding to the agreement achievement intention degree in the waiting queue when it is lower than a preset low intention threshold, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low intention customer, so as to update the customer source data, wherein the customer source data includes at least one customer and the identification content corresponding thereto; The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct to return visit reminders to the customers corresponding to the orders in the return visit reminder queue.

[0008] In a possible implementation, determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data includes: Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors in the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate a long-term dependency relationship in the interactive audio data; Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data; The speech feature data and the text feature data are calculated by a preset cross attention model to determine a speech attention weight matrix and a text attention weight matrix; Determine a corresponding speech attention weight feature based on the speech attention weight matrix, and determine a corresponding text attention weight feature based on the text attention weight matrix; The speech attention weight feature and the text attention weight feature are spliced ​​to determine the degree of intention to reach an agreement on the target order based on the splicing result.

[0009] In a possible implementation, the order data includes order delivery date, clothing type, clothing quantity, and clothing size; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including: quantifying the clothing type into at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size into the material requirement of the target order, and forming the material requirement data in the order requirement data with the clothing material and the material requirement; Querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material; When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0010] In a possible implementation, the adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When it is found that the material database does not completely have the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the abnormal demand condition, and then a corresponding material adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the material adjustment countersignature instruction and adjusts the agreement data before countersigning; When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

[0011] In a possible implementation, the determining, based on the order data, the production scheduling data corresponding to when the production efficiency data in the garment production process reaches a preset high efficiency condition includes: Determine the correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; Based on the order data, construct a production efficiency model of the target order, wherein the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; Building a scheduling model based on the production efficiency model of at least one target order currently to be processed; The scheduling model is iteratively solved, and the production scheduling data corresponding to the production efficiency data of the target order reaching the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing the production time and maximizing the utilization rate of the processing equipment, and the production scheduling data is used to indicate the processing amount of any clothing material on any processing equipment.

[0012] In a possible implementation, constructing the production efficiency model of the target order based on the order data includes: Acquire the call rate, equipment processing efficiency data and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data is used to indicate the processing time required for the processing equipment to process a specified clothing material of unit mass, and the material processing efficiency data is used to indicate the mass of any clothing material processed in unit time; Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material; Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material demand data of the target order; Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0013] In a possible implementation, the adjustment counter-signature instruction includes a demand adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When it is determined that the production scheduling data reaches the order demand data, production is performed according to the production scheduling data, wherein the order demand data includes time limit data related to the order delivery date, operation requirement data and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data; When it is determined that the production scheduling data does not meet any of the order demand data, it is confirmed that the order data meets the demand abnormality condition, then a corresponding demand adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction and updates the agreement data and then countersigns; When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is the updated agreement data, the order data is regenerated based on the updated agreement data.

[0014] In a possible implementation, the adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When a change is detected in the agreement data, it is confirmed that the order data meets the demand change condition, and a corresponding change adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data; When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

[0015] In a second aspect, the present application provides a system for processing clothing customization orders, including: a processing device and at least one countersignature terminal; The processing device is used to obtain the agreement data of the target order, wherein the agreement data carries the agreement countersigning instruction initiated by any countersigning terminal; The countersignature terminal is used to respond to the agreement countersignature instruction to countersign and then generate an agreement countersignature result; The processing device is used to generate corresponding order data based on the agreement data when it is detected that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning; and initiate a corresponding adjustment countersigning instruction and send it to the countersigning terminal when it is detected that the order data meets any one of the order re-planning conditions, wherein the order re-planning conditions include a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data; The countersignature terminal is used to countersign in response to the adjustment countersignature instruction and then generate an adjustment countersignature result; The processing device is used to regenerate the order data of the target order based on the obtained adjustment counter-signing result, and perform production according to the updated order data.

[0016] The processing method and system of clothing customization orders provided in the embodiment of the present application counter-signs the protocol data by responding to the protocol counter-signing instruction, and the generation of order data based on the protocol data is triggered by the protocol counter-signing result, and then when it is detected that the order data meets any order re-planning condition, the adjustment counter-signing instruction is initiated, so as to regenerate the order data of the target order based on the adjustment counter-signing result, and produce according to the updated order data, so as to synchronize the data generated in the counter-signing process to the order management, and realize the integration of order management and counter-signing. In this way, it is different from the independent order management system and protocol counter-signing system in the prior art, solves the problem of information asynchrony in the existing clothing production processing method, can be applied to the scene of clothing customization orders, realizes adaptive synchronous scheduling, and can effectively improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for processing a clothing customization order provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a system for processing customized clothing orders provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Figure 1 A flowchart of a method for processing a customized clothing order is provided in an embodiment of the present application. The method for processing a customized clothing order is used for a processing device, and the method includes steps S101 to S104.

[0020] S101. Acquire the agreement data of the target order, where the agreement data carries an agreement countersigning instruction initiated by any countersigning terminal.

[0021] It should be noted that, unlike the independent order management systems and agreement counter-signing systems in the prior art, the processing device can be an electronic device that can perform operations such as order processing and counter-signing processes. The processing device integrates order management and counter-signing, improves data synchronization in the clothing production process, and avoids production errors caused by data asynchrony.

[0022] The counter-signing terminal can be a terminal device used by the client or the work executor (such as the agreement communication personnel, production personnel, etc.). During the counter-signing process, any counter-signing terminal or processing device initiates a counter-signing instruction, and the counter-signing terminal related to the counter-signing instruction responds to the counter-signing instruction to counter-sign.

[0023] In this application, the agreement data may be in the form of text such as an electronic agreement or in the form of audio, that is, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement. Specifically, the content involved in the interactive audio data and the electronic agreement data may include the name of the clothing product in the order, the order quantity, the unit price of the clothing product, the total price of the clothing product, the order delivery date, the remittance address, the delivery method, the liability for breach of contract, etc., and this application does not limit this.

[0024] S102. When it is detected that the agreement countersigning result is that the electronic agreement corresponding to the target order has been reached, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction.

[0025] In this application, any co-signing terminal initiates an agreement co-signing instruction, and the processing device responds after receiving the agreement co-signing instruction, and sends the agreement co-signing instruction to other co-signing terminals, so that the co-signing terminals perform multi-party co-signing based on the agreement data, and generate the corresponding agreement co-signing result and return it to the processing device. It should be noted that during the co-signing process, the co-signing terminal reviews whether the electronic agreement in the agreement data has been reached, and when multiple parties determine that the electronic agreement has been reached, it generates an agreement co-signing result indicating that the electronic agreement has been reached.

[0026] For example, the co-signing terminal A corresponding to the business personnel uploads the agreement data to the processing device and initiates the agreement co-signing instruction. Then the co-signing terminal where the customer is located and the co-signing terminal C corresponding to the process personnel need to review and co-sign the content of the electronic agreement. When both confirm that the electronic agreement has been reached, the agreement co-signing result indicating that the electronic agreement has been reached is fed back to the processing device, so that when the processing device recognizes that the electronic agreement has been reached, it triggers the generation of corresponding order data based on the agreement data.

[0027] Therefore, this application triggers the generation of order data through the agreement signing results, uses the signing results as the control factor of order management, realizes the mutual integration of signing and order management in data and process, improves data consistency, and realizes adaptive synchronous scheduling.

[0028] In an optional embodiment, the key order fields in the agreement data are extracted, and the key order fields are queried for the corresponding order template, thereby mapping the agreement data to the order template to form order data. Therefore, this embodiment generates an order that matches the agreement requirements by keyword matching and template matching. The order data includes information such as order date, delivery date, clothing type, clothing quantity, size, etc., so as to quickly screen out order information that meets the agreement requirements and improve processing efficiency.

[0029] S103. When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes an abnormal demand condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data.

[0030] S104. Based on the obtained adjustment counter-signing result, regenerate the order data of the target order, and perform production according to the updated order data, wherein the adjustment counter-signing result is generated after the counter-signing terminal responds to the adjustment counter-signing instruction and counter-signs.

[0031] In this application, order demand data may be material demand data related to order materials, time limit data related to order delivery date, operation requirement data and effect requirement data. The operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data. This application does not limit this. Demand abnormality conditions include abnormal conditions that represent completion time exceeding the order delivery date, abnormal operation conditions that do not meet the operation requirement data, and abnormal effect conditions that do not meet the effect requirement data. Demand change conditions represent the conditions under which the protocol data (such as an electronic protocol) is changed.

[0032] It is necessary to explain whether the order data meets the order re-planning conditions, such as whether the order materials have reasonable inventory, whether the production scheduling data of the order can be delivered within the time limit data, whether the agreement data has changed, etc. Then, when it is detected that at least one order re-planning condition is met, the adjustment countersignature instruction is triggered and sent to the corresponding countersignature terminal, so that the countersignature terminal can revise the agreement data, review, confirm and countersign the revised agreement data, and generate an adjustment countersignature result containing the confirmed revised agreement data.

[0033] Therefore, this application triggers the initiation of the counter-signing process when the order data meets any order re-planning conditions, and obtains the counter-signing result after multiple parties counter-sign, so as to update the order data based on the counter-signing result, so that production is carried out based on the updated order data, ensuring that the production process can quickly adapt to changes, avoiding production errors caused by delays, and achieving timely response and adjustment. At the same time, production is carried out based on the updated order data, and the data generated in the counter-signing process is synchronously updated to the order management, so that the order management and counter-signing can be integrated and operated, and each link in the clothing production can be interdependent, which improves the data response efficiency and thus improves the production efficiency.

[0034] The processing method of clothing customization order provided by the present application countersigns the protocol data by responding to the protocol countersigning instruction, and the generation of order data based on the protocol data is triggered by the protocol countersigning result, and then when it is detected that the order data meets any order re-planning condition, the adjustment countersigning instruction is initiated, so as to regenerate the order data of the target order based on the adjustment countersigning result, and produce according to the updated order data, so as to synchronize the data generated in the countersigning process to the order management, and realize the integration of order management and countersigning. In this way, it is different from the independent order management system and protocol countersigning system in the prior art, solves the problem of information asynchrony in the existing clothing production processing method, can be applied to the scene of clothing customization order, realizes adaptive synchronous scheduling, and can effectively improve production efficiency.

[0035] In some embodiments, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, and the interactive audio data is used to record the voice communication process of the electronic agreement and / or the target order. Specifically, the method further includes: When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, an intention analysis is performed on the interactive audio data of the target order; When it is analyzed that the electronic agreement meets the preset condition of the tendency to achieve the goal, the target order is added to the waiting queue; Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data; Clearing the target order corresponding to the agreement achievement intention degree in the waiting queue when it is lower than a preset low intention threshold, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low intention customer, so as to update the customer source data, wherein the customer source data includes at least one customer and the identification content corresponding thereto; The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct to return visit reminders to the customers corresponding to the orders in the return visit reminder queue.

[0036] In this embodiment, during the process of the countersigning terminal responding to the agreement countersigning instruction to countersign the agreement data with multiple parties, if the review confirms that the electronic agreement has not been reached, an agreement countersigning result is generated to indicate that the electronic agreement has not been reached. Subsequently, after receiving the agreement countersigning result, the processing device performs an intention analysis on the interactive audio data (such as a business negotiation recording) contained in the agreement data. Optionally, if the customer does not directly express a refusal during the communication process through voice recognition, it is considered that the electronic agreement meets the condition of the tendency to reach an agreement, and there is a possibility of reaching an agreement. Similarly, if the customer directly expresses the intention of refusal during the communication process, it is recognized that the electronic agreement does not meet the condition of the tendency to reach an agreement.

[0037] Furthermore, the orders corresponding to the electronic agreements that meet the conditions for the tendency to reach an agreement are added to the waiting queue to further judge the customer's willingness and enthusiasm. Specifically, the electronic agreement data and the interactive audio data are subjected to feature analysis to determine the intention to reach an agreement. Among them, the intention to reach an agreement can be the customer's intention score for reaching an agreement, such as 0-100. Then, by setting a threshold, the electronic agreements whose intention to reach an agreement is lower than the low intention threshold are regarded as invalid agreements, cleaned, and fed back to the relevant business personnel in the form of agreement termination (such as an agreement termination instruction) to update the customer source data (marked as a low-intention customer). In addition, the remaining agreements in the waiting queue are sorted from large to small according to the intention to reach an agreement, and the corresponding return visit reminder queue and return visit reminder instruction are generated to achieve regular push of customer return visit reminders in the sorting order to promote the agreement.

[0038] Therefore, this embodiment detects that the result of the agreement signing is that the electronic agreement has not been reached, then performs intention analysis on orders with a tendency to be reached, removes orders with a low intention to reach the agreement, and reminds customers to return visit based on the degree of intention to reach the agreement, thereby realizing potential data mining and intention mining and improving data utilization.

[0039] In some embodiments, determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data includes: Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors in the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate a long-term dependency relationship in the interactive audio data; Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data; The speech feature data and the text feature data are calculated by a preset cross attention model to determine a speech attention weight matrix and a text attention weight matrix; Determine a corresponding speech attention weight feature based on the speech attention weight matrix, and determine a corresponding text attention weight feature based on the text attention weight matrix; The speech attention weight feature and the text attention weight feature are spliced ​​to determine the degree of intention to reach an agreement on the target order based on the splicing result.

[0040] In this embodiment, the first feature extraction model includes a convolutional neural network and a recurrent neural network arranged in sequence. Specifically, the interactive audio data is feature extracted by the convolutional neural network to obtain a feature vector, and the feature vector is secondarily analyzed by the recurrent neural network to obtain speech feature data. Therefore, this embodiment extracts features from the interactive audio data by the first feature extraction model, thereby improving the accuracy of data extraction.

[0041] Exemplarily, the operation of the convolutional neural network is determined by the following formula: in, is the feature vector, Represents the operation of convolutional neural network, Represents a sequence of interactive audio data sampled at a unit step size.

[0042] The operation of the recurrent neural network is determined by the following formula: in, is the voice feature data, Represents the operation of a recurrent neural network.

[0043] In this embodiment, the second feature extraction model includes a Bert model and a recurrent neural network arranged in sequence. Specifically, the electronic agreement data is embedded by the Bert model to obtain a text vector, and the text vector is feature analyzed by the recurrent neural network to obtain text feature data. Therefore, this embodiment extracts features from the electronic agreement data through the second feature extraction model, thereby improving the accuracy of data extraction.

[0044] Furthermore, this embodiment calculates the speech feature data and text feature data through a cross-attention model (the model is built on the cross-attention mechanism) to obtain a speech attention weight matrix and a text attention weight matrix. Then, through the statistical pooling layer, the speech attention weight feature and the text attention weight feature are obtained, wherein the attention weight feature includes the mean and standard deviation features of the attention weight. Then, the speech attention weight feature and the text attention weight feature are spliced ​​in the channel dimension, and then the splicing result is processed in combination with multiple fully connected layers to obtain the customer's intention score for reaching an agreement, that is, the intention to reach an agreement.

[0045] Therefore, this embodiment performs feature extraction on the interactive audio data through the first feature extraction model, performs feature extraction on the electronic agreement data through the second feature extraction model, and determines the voice attention weight features and the text attention weight features, so as to obtain the intention degree of agreement reaching, achieve the accuracy of feature extraction, accurately reflect the intention of the agreement data, and improve the accuracy of intent analysis.

[0046] In some embodiments, the order data includes order delivery date, clothing type, clothing quantity and clothing size; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including: quantifying the clothing type into at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size into the material requirement of the target order, and forming the material requirement data in the order requirement data with the clothing material and the material requirement; Querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material; When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0047] In this embodiment, the material demand data includes at least one clothing material in the target order and the material demand of each clothing material. Then, the material database is queried based on the material demand data. When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, it means that the inventory is sufficient to process the target order, and the corresponding production scheduling data is generated based on the order data.

[0048] Therefore, this embodiment determines whether the order data meets the material demand data to confirm whether the order re-planning conditions are met, thereby eliminating delays caused by material shortages in the initial stage, achieving timely response and adjustment, reducing production losses, and improving production efficiency.

[0049] Based on the above embodiment, in some embodiments, the adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When it is found that the material database does not completely have the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the abnormal demand condition, and then a corresponding material adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the material adjustment countersignature instruction and adjusts the agreement data before countersigning; When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

[0050] In this embodiment, when it is found that the material database does not have all the clothing materials, or the material demand of any clothing material is lower than the material inventory, it indicates that the material inventory of the target order is in short supply. Then, it is confirmed that the order data meets the order re-planning conditions (i.e., the abnormal demand conditions corresponding to the material demand data), and a material adjustment countersignature instruction is triggered.

[0051] In response to the material adjustment countersignature instruction, the countersignature terminal can adjust the material demand data in the agreement data, review and countersign the adjusted agreement data, and return the material adjustment countersignature result to the processing device. Then, based on the material adjustment countersignature result including the adjusted agreement data, the order data is regenerated, and the material demand data indicated by the updated order data is determined to query the material inventory status in the material database.

[0052] Therefore, this embodiment queries the material shortage of the target order in the material database to confirm that the material demand data corresponding to the order data meets the abnormal demand conditions, and then sends a material adjustment counter-signing instruction, and regenerates the order data based on the adjusted protocol data contained in the material adjustment counter-signing result, thereby realizing synchronous scheduling, avoiding data inconsistency, and improving processing efficiency and generation efficiency.

[0053] In some embodiments, the determining, based on the order data, the production scheduling data corresponding to when the production efficiency data in the garment production process reaches a preset high efficiency condition includes: Determine the correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; Based on the order data, construct a production efficiency model of the target order, wherein the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; Building a scheduling model based on the production efficiency model of at least one target order currently to be processed; The scheduling model is iteratively solved, and the production scheduling data corresponding to the production efficiency data of the target order reaching the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing the production time and maximizing the utilization rate of the processing equipment, and the production scheduling data is used to indicate the processing amount of any clothing material on any processing equipment.

[0054] In this embodiment, the correlation factors represent parameters in the production process, such as the consumption of a certain material or the scheduling utilization rate of processing equipment. Based on the order data, the production efficiency model of the target order under the influence of the correlation factors is determined. The production efficiency model can include production efficiency, cost function, etc. under the correlation factors. Then, based on the current multiple target orders to be processed and the corresponding production efficiency models, the scheduling model is determined. It should be noted that the scheduling model is used to realize the collaborative planning of the current multiple target orders to be processed, aiming to improve the overall processing efficiency while taking into account the improvement of individual production efficiency.

[0055] Furthermore, the scheduling model can be iteratively solved using existing optimization algorithms, such as ant colony algorithms, to obtain the production scheduling data of multiple target orders to be processed, that is, the distribution and processing conditions, such as the processing volume of the i-th material in the j-th processing equipment. Specifically, in the process of solving the scheduling model, high-efficiency conditions are set, such as minimum production time, maximum processing equipment utilization, etc., so that the corresponding production scheduling data when the high-efficiency conditions are met can be screened out.

[0056] Therefore, this embodiment constructs a production efficiency model of a target order and a scheduling model for collaborative production of multiple target orders by determining associated factors, thereby improving the rationality and efficiency of production scheduling and improving equipment utilization.

[0057] In some embodiments, constructing the production efficiency model of the target order based on the order data includes: Acquire the call rate, equipment processing efficiency data and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data is used to indicate the processing time required for the processing equipment to process a specified clothing material of unit mass, and the material processing efficiency data is used to indicate the mass of any clothing material processed in unit time; Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material; Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material demand data of the target order; Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0058] In this embodiment, the production efficiency model is determined by the following formula: in, represents the production efficiency model of the kth order, M represents the number of associated factors, Represents the model function of the k-th order under the M-th associated factor.

[0059] Optionally, by constructing an equipment processing efficiency model as the model function, the production efficiency model is represented by the equipment processing efficiency model under the influence of multiple related factors. The model function can be determined by the following formula: in, Indicates clothing material M, represents the equipment processing efficiency model, It represents the equipment processing efficiency data, that is, it indicates the processing time required for the i-th processing equipment to process a unit mass of the specified clothing material M, and n is the number of processing equipment.

[0060] Optionally, by constructing a material processing efficiency model as the model function, the production efficiency model is represented as a material processing efficiency model under the influence of multiple related factors. The model function can be determined by the following formula: in, represents the material processing efficiency model, represents the call rate of the Mth processing equipment, Represents material processing efficiency data, that is, it is used to indicate the quality of processing the jth type of clothing material per unit time. represents the material demand of the jth type of clothing material, and z represents the number of types of clothing materials.

[0061] Optionally, a fusion model is generated by using a material processing efficiency model and an equipment processing efficiency model, and based on the fusion model as the model function, the production efficiency model is represented as a fusion model under the influence of multiple related factors.

[0062] Therefore, this embodiment constructs a material processing efficiency model and an equipment processing efficiency model to construct a production efficiency model, thereby improving the accuracy of the model and facilitating improving the efficiency of production scheduling.

[0063] In some embodiments, the adjustment counter-signature instruction includes a demand adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When it is determined that the production scheduling data reaches the order demand data, production is performed according to the production scheduling data, wherein the order demand data includes time limit data related to the order delivery date, operation requirement data and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data; When it is determined that the production scheduling data does not meet any of the order demand data, it is confirmed that the order data meets the demand abnormality condition, then a corresponding demand adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction and updates the agreement data and then countersigns; When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is the updated agreement data, the order data is regenerated based on the updated agreement data.

[0064] In this embodiment, it is detected whether the production scheduling data meets the order requirement data, such as whether it can be delivered within the time limit data, whether it meets the production operation requirements, whether it meets the effect requirements, etc., but not limited thereto. Then, when it is detected that the production scheduling data meets the order requirement data, it means that the production scheduling process and results meet the order requirements, and production is carried out according to the production scheduling data.

[0065] Therefore, this embodiment achieves timely response and adjustment, reduces production losses, and improves production efficiency by planning the production scheduling data of the order and checking whether the production scheduling data meets the order demand data.

[0066] Optionally, when it is detected that the production scheduling data does not meet the order demand data, such as overtime delivery, substandard production process, and results that do not meet requirements, the order data is confirmed to meet the order re-planning conditions (i.e., the abnormal demand conditions corresponding to the order demand data), and a demand adjustment countersignature instruction is triggered.

[0067] In response to this, the countersignature terminal responds to the demand adjustment countersignature instruction, can adjust the delivery date, product effect and other contents in the agreement data, and review and countersign the updated agreement data, and return the demand adjustment countersignature result to the processing device. Then, based on the demand adjustment countersignature result including the updated agreement data, the order data is regenerated, and after determining that the updated order data meets the material demand data, the production scheduling data is regenerated to achieve the reallocation of the processing situation.

[0068] Optionally, when it is detected that the production scheduling data does not meet the order demand data, the target order can be added to a waiting queue to perform an intention analysis on the protocol data.

[0069] Therefore, in this embodiment, the production scheduling data does not meet the order demand data to confirm that the order demand data corresponding to the order data meets the demand abnormality condition, and then sends a demand adjustment counter-signing instruction, and regenerates the order data and production scheduling data based on the updated protocol data contained in the demand adjustment counter-signing result, to achieve synchronous scheduling, avoid data inconsistency, and improve processing efficiency and generation efficiency.

[0070] In some embodiments, the adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, further comprising: When a change is detected in the agreement data, it is confirmed that the order data meets the demand change condition, and a corresponding change adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data; When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

[0071] In this embodiment, when a change in the protocol data is detected during any process processing, that is, a change in user demand, and the order data is confirmed to meet the demand change conditions, a change adjustment countersignature instruction is generated. Then, the countersignature terminal responds to the change adjustment countersignature instruction, reviews and countersigns the updated protocol data (that is, the changed content in the protocol data), and returns the change adjustment countersignature result to the processing device. Then, based on the change adjustment countersignature result including the changed protocol data, the order data is regenerated, and the updated order data and production scheduling data are determined to achieve the reallocation of the processing situation.

[0072] Therefore, this embodiment detects changes in the protocol data to confirm that the order data meets the demand change conditions, and then sends a change adjustment countersignature instruction, and regenerates the order data and production scheduling data based on the changed protocol data included in the change adjustment countersignature result, to achieve synchronous scheduling, avoid data inconsistency, improve processing efficiency and generation efficiency, and ensure that production efficiency continues to remain optimal.

[0073] Optionally, a delivery countersignature is initiated after production is completed, so that the countersignature equipment conducts multi-party review and countersignature on the delivery countersignature to complete the entire production and delivery process of the order.

[0074] Figure 2 A schematic diagram of a system for processing a clothing customization order provided in an embodiment of the present application, wherein the system 200 for processing a clothing customization order comprises: a processing device 201 and at least one countersigning terminal 202; The processing device 201 is used to obtain the agreement data of the target order, where the agreement data carries the agreement countersigning instruction initiated by any countersigning terminal; The countersigning terminal 202 is used to respond to the agreement countersigning instruction to countersign and then generate an agreement countersigning result; The processing device 201 is used for, when it is detected that the electronic agreement corresponding to the target order has been reached as a result of the agreement countersigning, generating corresponding order data based on the agreement data; when it is detected that the order data meets any one of the order re-planning conditions, initiating a corresponding adjustment countersigning instruction and sending it to the countersigning terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data; The countersigning terminal 202 is used to countersign in response to the adjustment countersigning instruction and then generate an adjustment countersigning result; The processing device 201 is used to regenerate the order data of the target order based on the obtained adjustment counter-signing result, and perform production according to the updated order data.

[0075] In some embodiments, the agreement data includes interactive audio data and electronic agreement data for the electronic agreement, and the interactive audio data is used to record the voice communication process of the electronic agreement and / or the target order; The processing device is further configured to perform intention analysis on the interactive audio data of the target order when it is detected that the agreement countersigning result is that the electronic agreement has not been reached; When it is analyzed that the electronic agreement meets the preset condition of the tendency to achieve the goal, the target order is added to the waiting queue; Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data; Clearing the target order corresponding to the agreement achievement intention degree in the waiting queue when it is lower than a preset low intention threshold, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low intention customer, so as to update the customer source data, wherein the customer source data includes at least one customer and the identification content corresponding thereto; The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct to return visit reminders to the customers corresponding to the orders in the return visit reminder queue.

[0076] In some embodiments, the processing device is further used to input the interactive audio data into a preset first feature extraction model to extract feature vectors in the interactive audio data, analyze the feature vectors, and output voice feature data, wherein the voice feature data is used to indicate a long-term dependency relationship in the interactive audio data; Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data; The speech feature data and the text feature data are calculated by a preset cross attention model to determine a speech attention weight matrix and a text attention weight matrix; Determine a corresponding speech attention weight feature based on the speech attention weight matrix, and determine a corresponding text attention weight feature based on the text attention weight matrix; The speech attention weight feature and the text attention weight feature are spliced ​​to determine the degree of intention to reach an agreement on the target order based on the splicing result.

[0077] In some embodiments, the order data includes order delivery date, clothing type, clothing quantity, and clothing size; The processing device is further used to quantify the clothing type into at least one clothing material required for the target order, quantify the clothing quantity and the clothing size into the material requirement of the target order, and form the material requirement data in the order requirement data with the clothing material and the material requirement; Querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material; When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

[0078] In some embodiments, the adjustment counter-signature instruction includes a material adjustment counter-signature instruction; The processing device is used to confirm that the order data meets the abnormal demand condition when it is found that the material database does not have all the clothing materials, or the material demand of any clothing material is lower than the material inventory, and then generate a corresponding material adjustment countersignature instruction and send it to the countersignature terminal; The countersignature terminal is used to respond to the material adjustment countersignature instruction, countersign the agreement data after adjustment, and generate a material adjustment countersignature result; The processing device is used to regenerate the order data based on the adjusted agreement data when it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data.

[0079] In some embodiments, the processing device is used to determine the associated factors of the target order in the production process, and the associated factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; Based on the order data, construct a production efficiency model of the target order, wherein the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; Building a scheduling model based on the production efficiency model of at least one target order currently to be processed; The scheduling model is iteratively solved, and the production scheduling data corresponding to the production efficiency data of the target order reaching the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing the production time and maximizing the utilization rate of the processing equipment, and the production scheduling data is used to indicate the processing amount of any clothing material on any processing equipment.

[0080] In some embodiments, the processing device is used to obtain the call rate, equipment processing efficiency data and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data is used to indicate the processing time required for the processing equipment to process a specified clothing material of unit mass, and the material processing efficiency data is used to indicate the quality of processing any clothing material per unit time; Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material; Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material demand data of the target order; Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

[0081] In some embodiments, the adjustment countersignature instruction includes a demand adjustment countersignature instruction; The processing device is used to perform production according to the production scheduling data when it is judged that the production scheduling data reaches the order demand data, wherein the order demand data includes time limit data, operation requirement data and effect requirement data related to the order delivery date, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data; when it is judged that the production scheduling data does not meet any of the order demand data, it is confirmed that the order data meets the demand abnormality condition, then a corresponding demand adjustment counter-signing instruction is generated and then sent to the counter-signing terminal; The countersigning terminal is used to respond to the demand adjustment countersigning instruction and countersign the updated protocol data; The processing device is used to regenerate the order data based on the updated protocol data when detecting that the demand adjustment counter-signing result sent by the counter-signing terminal is the updated protocol data.

[0082] In some embodiments, the adjustment countersignature instruction includes a change adjustment countersignature instruction; The processing device is used to, when detecting that the agreement data has changed, confirm that the order data meets the requirement change condition, generate a corresponding change adjustment countersignature instruction, and then send it to the countersignature terminal; The countersigning terminal is used to countersign the changed protocol data in response to the change adjustment countersigning instruction; The processing device is used to regenerate the order data based on the changed agreement data when it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data.

[0083] The system of the embodiments of the present application can execute the method provided by the embodiments of the present application, and the implementation principles are similar. The actions performed by each device in the system of each embodiment of the present application correspond to the steps in the method of each embodiment of the present application. For the detailed functional description of each device of the system, please refer to the description in the corresponding method shown in the previous text, which will not be repeated here.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for processing a clothing customization order, characterized in that: For processing equipment, including: Acquire the agreement data of the target order, wherein the agreement data carries the agreement countersigning instruction initiated from any countersigning terminal; When it is detected that the agreement countersigning result is that the electronic agreement corresponding to the target order has been reached, corresponding order data is generated based on the agreement data, wherein the agreement countersigning result is generated after countersigning by at least one other countersigning terminal in response to the agreement countersigning instruction; When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data; Based on the obtained adjustment counter-signing result, the order data of the target order is regenerated, and production is performed according to the updated order data, wherein the adjustment counter-signing result is generated after the counter-signing terminal responds to the adjustment counter-signing instruction and counter-signs.

2. The method for processing clothing customization orders according to claim 1, characterized in that: The agreement data includes interactive audio data and electronic agreement data for the electronic agreement, wherein the interactive audio data is used to record the voice communication process for the electronic agreement and / or the target order; The method further comprises: When it is detected that the electronic agreement has not been reached as a result of the agreement countersigning, an intention analysis is performed on the interactive audio data of the target order; When it is analyzed that the electronic agreement meets the preset condition of the tendency to achieve the goal, the target order is added to the waiting queue; Determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data; Clearing the target order corresponding to the agreement achievement intention degree in the waiting queue when it is lower than a preset low intention threshold, generating an agreement termination instruction for instructing the termination of the cleared target order, and identifying the customer corresponding to the cleared target order as a low intention customer, so as to update the customer source data, wherein the customer source data includes at least one customer and the identification content corresponding thereto; The agreement reaching intentions of the remaining orders in the waiting queue are sorted from large to small, and a corresponding return visit reminder queue and return visit reminder instruction are generated. The return visit reminder instruction is used to instruct to return visit reminders to the customers corresponding to the orders in the return visit reminder queue.

3. The method for processing clothing customization orders according to claim 2, characterized in that: The step of determining the degree of intention to reach an agreement based on the interactive audio data and the electronic agreement data includes: Inputting the interactive audio data into a preset first feature extraction model to extract feature vectors in the interactive audio data, analyzing the feature vectors, and outputting speech feature data, wherein the speech feature data is used to indicate a long-term dependency relationship in the interactive audio data; Inputting the electronic agreement data into a preset second feature extraction model to perform embedding value calculation on the electronic agreement data to obtain a text vector, and performing feature extraction on the text vector to output text feature data, wherein the text feature data is used to indicate a long-term dependency relationship in the electronic agreement data; The speech feature data and the text feature data are calculated by a preset cross attention model to determine a speech attention weight matrix and a text attention weight matrix; Determine a corresponding speech attention weight feature based on the speech attention weight matrix, and determine a corresponding text attention weight feature based on the text attention weight matrix; The speech attention weight feature and the text attention weight feature are spliced ​​to determine the degree of intention to reach an agreement on the target order based on the splicing result.

4. The method for processing clothing customization orders according to claim 3, characterized in that: The order data includes order delivery date, clothing type, clothing quantity and clothing size; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment countersignature instruction is initiated and sent to the countersignature terminal, including: quantifying the clothing type into at least one clothing material required for the target order, quantifying the clothing quantity and the clothing size into the material requirement of the target order, and forming the material requirement data in the order requirement data with the clothing material and the material requirement; Querying a material database based on the material demand data, wherein the material database is configured with at least one material and the material inventory of the material; When it is found that the material database has all clothing materials and the material demand of each clothing material is higher than the material inventory, the production scheduling data corresponding to the production efficiency data in the clothing production process reaching the preset high-efficiency conditions is determined based on the order data.

5. The method for processing clothing customization orders according to claim 4, characterized in that: The adjustment counter-signature instruction includes a material adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, and further includes: When it is found that the material database does not completely have the clothing materials, or the material demand of any of the clothing materials is lower than the material inventory, it is confirmed that the order data meets the abnormal demand condition, and then a corresponding material adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the material adjustment countersignature instruction and adjusts the agreement data before countersigning; When it is detected that the material adjustment counter-signing result sent by the counter-signing terminal is the adjusted agreement data, the order data is regenerated based on the adjusted agreement data.

6. The method for processing clothing customization orders according to claim 5, characterized in that: The step of determining, based on the order data, the production scheduling data corresponding to when the production efficiency data in the garment production process reaches a preset high efficiency condition comprises: Determine the correlation factors of the target order in the production process, wherein the correlation factors include the consumption of any clothing material and the scheduling utilization rate of any processing equipment; Based on the order data, construct a production efficiency model of the target order, wherein the production efficiency model is used to indicate the production efficiency data of the target order under the influence of the associated factors; Building a scheduling model based on the production efficiency model of at least one target order currently to be processed; The scheduling model is iteratively solved, and the production scheduling data corresponding to the production efficiency data of the target order reaching the high-efficiency condition is screened out, wherein the high-efficiency condition includes at least one of minimizing the production time and maximizing the utilization rate of the processing equipment, and the production scheduling data is used to indicate the processing amount of any clothing material on any processing equipment.

7. The method for processing a customized clothing order according to claim 6, characterized in that: The step of constructing a production efficiency model for the target order based on the order data includes: Acquire the call rate, equipment processing efficiency data and material processing efficiency data of the processing equipment, wherein the equipment processing efficiency data is used to indicate the processing time required for the processing equipment to process a specified clothing material of unit mass, and the material processing efficiency data is used to indicate the mass of any clothing material processed in unit time; Determining an equipment processing efficiency model for the target order based on any clothing material and equipment processing efficiency data of a processing equipment used to process the clothing material; Determining a material processing efficiency model for the target order based on the call rate of the processing equipment, the material processing efficiency data, and the material demand data of the target order; Based on the equipment processing efficiency model and / or the material processing efficiency model, a production efficiency model of the target order is constructed.

8. The method for processing clothing customization orders according to claim 7, characterized in that: The adjustment counter-signature instruction includes a demand adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, and further includes: When it is determined that the production scheduling data reaches the order demand data, production is performed according to the production scheduling data, wherein the order demand data includes time limit data related to the order delivery date, operation requirement data and effect requirement data, the operation requirement data is used to indicate the operation requirements of the target order in the production process, and the effect requirement data includes completion requirement data and quality requirement data; When it is determined that the production scheduling data does not meet any of the order demand data, it is confirmed that the order data meets the demand abnormality condition, then a corresponding demand adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the demand adjustment countersignature instruction and updates the agreement data and then countersigns; When it is detected that the demand adjustment counter-signing result sent by the counter-signing terminal is the updated agreement data, the order data is regenerated based on the updated agreement data.

9. The method for processing clothing customization orders according to claim 1, characterized in that: The adjustment counter-signature instruction includes a change adjustment counter-signature instruction; when it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signature instruction is initiated and sent to the counter-signature terminal, and further includes: When a change is detected in the agreement data, it is confirmed that the order data meets the demand change condition, and a corresponding change adjustment countersignature instruction is generated, and then sent to the countersignature terminal, so that the countersignature terminal responds to the change adjustment countersignature instruction and countersigns the changed agreement data; When it is detected that the change adjustment counter-signing result sent by the counter-signing terminal is the changed agreement data, the order data is regenerated based on the changed agreement data.

10. A system for processing customized clothing orders, characterized in that: include: processing equipment and at least one countersigning terminal; The processing device is used to obtain the agreement data of the target order, wherein the agreement data carries the agreement countersigning instruction initiated by any countersigning terminal; The countersignature terminal is used to respond to the agreement countersignature instruction to countersign and then generate an agreement countersignature result; The processing device is used to generate corresponding order data based on the agreement data when detecting that the agreement countersigning result is that the electronic agreement corresponding to the target order has been reached; When it is detected that the order data meets any order re-planning condition, a corresponding adjustment counter-signing instruction is initiated and sent to the counter-signing terminal, wherein the order re-planning condition includes a demand abnormality condition corresponding to the order demand data indicated by the order data and a demand change condition corresponding to the agreement data; The countersignature terminal is used to respond to the adjustment countersignature instruction to countersign and then generate an adjustment countersignature result; The processing device is used to regenerate the order data of the target order based on the obtained adjustment counter-signing result, and perform production according to the updated order data.

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